A two-stage pooled panel data estimator of demand elasticities

Soderbery (2015) extended this estimator and created a routine which was shown to be more robust to data outliers when the number of time periods is small or moderate. In this paper, we extend the Feenstra/Soderbery (F/S) estimator along two important dimensions to obtain a more efficient estimator: we handle the cases where there are no simultaneity problems, i.e. when supply is either elastic or inelastic, and we generalize the current practice of choosing a particular reference variety by creating a pooled estimator across all possible reference varieties. Using a Monte Carlo study, we show that our proposed estimator reduces the RMSE compared to the F/S estimator by between 60 and 90 percent across the whole parameter space.

The STATA code to reproduce our findings can be found in the files below. The code is written in a general form that allows users to easily adapt our proposed 2SP estimator to their data.

feen94_LIMLhybrid_sim_alfa_beta(-1.0).do

feen94_pooledGMM_sim_alfa_beta_(-1).do

mata_LIMLhybrid.do

random_draw_n200_t100_s100.7z